Clinical outcomes following COVID-19 infection in ethnic minority groups in the UK: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVES: This study evaluated the differences in clinical outcomes of COVID-19 infection between ethnic minorities and the White ethnic group in the UK. STUDY DESIGN: Systematic review and meta-analysis. METHODS: This study included adult residents in the UK with confirmed COVID-19 infection. The outcomes evaluated in this study were mortality, intensive care unit (ICU) admission and invasive mechanical ventilation (IMV). Outcome data were compared between individuals from ethnic minority groups and individuals from a White ethnic background. MEDLINE, Embase, Cochrane, medRxiv and PROSPERO were searched for articles published between May 2020 and April 2021. The risk of bias was evaluated using the Newcastle-Ottawa Scale checklist. PROSPERO ID: CRD42021248117. RESULTS: Fourteen studies (767,177 participants) were included in the current review. In the adjusted analysis, the pooled odds ratio (OR) for mortality following COVID-19 infection was higher for Black (OR 1.83, 95% confidence interval [CI]: 1.21-2.76, number of studies [k] = 6), Asian (OR 1.16, 95% CI: 0.85-1.57, k = 6) and Mixed and Other (MO) ethnic groups (OR 1.12, 95% CI: 1.04-1.20, k = 5) compared with the White ethnic group. The adjusted and unadjusted ORs of ICU admission for many of the ethnic minority groups were more than double the OR values for the White ethnic group (Black ethnic group = OR 2.32, 95% CI: 1.73-3.11, k = 5; Asian ethnic group = OR 2.34, 95% CI: 1.89-2.90, k = 5; and MO ethnic group = OR 2.26, 95% CI: 1.64-3.11, k = 4). In the adjusted analysis for IMV, the ORs were similarly significantly raised in ethnic minority groups compared with the White ethnic group (Black ethic group = OR 2.03, 95% CI: 1.80-2.29, k = 3; Asian ethnic group = OR 1.84, 95% CI: 1.20-2.80, k = 3; and MO ethnic group = OR 2.09, 95% CI: 1.35-3.22, k = 3). CONCLUSION: This review found that in the UK, Black, Asian and MO ethnic groups experienced increased COVID-19-related disease severity and mortality compared with the White ethnic group majority.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.032 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".